Recognizing complex patterns.
Abstract
How the brain recognizes complex patterns in the environment is a central, but little understood question in neuroscience. The problem is of great significance for a host of applications such as biometric-based access control, autonomous robots and content-based information management. Although some headway in these directions has been made, the current artificial systems do not match the robustness and versatility of their biological counterparts. Here I examine recognition tasks drawn from two different sensory modalities--face recognition and speaker/speech recognition. The goal is to characterize the present state of artificial recognition technologies for these tasks, the influence of neuroscience on the design of these systems and the key challenges they face.
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Humans can extract complex information, such as identifying human faces, from relatively poor-quality images by using specific cues and multiple visual features.
“Thus, we can extract complex information, such as identifying human faces, from relatively poor-quality images by using specific cues and multiple visual features (Sinha, 2002).”
From Toward Long-Term Communication With the Brain in the Blind by Intracortical Stimulation: Challenges and Future Prospects (2020) · cites this paper as Sinha, 2002
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- Authors
- Sinha, P.
- Affiliations
- Massachusetts Institute of Technology (US)
- Corresponding author
- Sinha, Pawan
- ORCID
- Sinha, Pawan
- Venue
- Nature Neuroscience
- Published
- 2002-10-28
- Volume
- 5
- Issue
- S11
- Pages
- 1093-1097
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- OpenAlex
- W1968603670
- Cited by
- 65
- References
- 43
- Citations by year
- 2026: 1 · 2025: 1 · 2023: 1 · 2022: 1 · 2021: 4 · 2020: 7 · 2019: 1 · 2018: 2 · 2017: 3 · 2016: 3 · 2015: 2 · 2014: 5 · 2013: 2 · 2012: 2
- FWCI
- 0.21
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Physical Sciences › Computer Science › Artificial Intelligence › Neural Networks and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Keywords
- pattern recognition, face recognition (cognition), speech recognition, speaker recognition, biometric access control, autonomous robots
- MeSH terms
- Animals, Artificial Intelligence, Brain, Face, Humans, Image Processing, Computer-Assisted, Neurosciences, Pattern Recognition, Visual, Speech Perception
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